A Fingerprint Detection Method by Fingerprint Ridge Orientation Check
- URL: http://arxiv.org/abs/2205.03019v1
- Date: Fri, 6 May 2022 05:19:41 GMT
- Title: A Fingerprint Detection Method by Fingerprint Ridge Orientation Check
- Authors: Kim JuSong, Ri IlYong
- Abstract summary: Fingerprint recognition technology has been studied for a long time, and its recognition rate has recently risen to a high level.
In this paper, we propose a fingerprint detection algorithm used in a fingerprint recognition system.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Fingerprints are popular among the biometric based systems due to ease of
acquisition, uniqueness and availability. Nowadays it is used in smart phone
security, digital payment and digital locker. Fingerprint recognition
technology has been studied for a long time, and its recognition rate has
recently risen to a high level. In particular, with the introduction of Deep
Neural Network technologies, the recognition rate that could not be reached
before was reached. In this paper, we propose a fingerprint detection algorithm
used in a fingerprint recognition system.
Related papers
- Fingerprinting and Tracing Shadows: The Development and Impact of Browser Fingerprinting on Digital Privacy [55.2480439325792]
Browser fingerprinting is a growing technique for identifying and tracking users online without traditional methods like cookies.
This paper gives an overview by examining the various fingerprinting techniques and analyzes the entropy and uniqueness of the collected data.
arXiv Detail & Related papers (2024-11-18T20:32:31Z) - Latent fingerprint enhancement for accurate minutiae detection [8.996826918574463]
We propose a novel approach that uses generative adversary networks (GANs) to redefine Latent Fingerprint Enhancement (LFE)
By directly optimising the minutiae information during the generation process, the model produces enhanced latent fingerprints that exhibit exceptional fidelity to ground-truth instances.
Our framework integrates minutiae locations and orientation fields, ensuring the preservation of both local and structural fingerprint features.
arXiv Detail & Related papers (2024-09-18T08:35:31Z) - Biometrics Employing Neural Network [0.0]
Fingerprints, iris and retina patterns, facial recognition, hand shapes, palm prints, and voice recognition are frequently used forms of biometrics.
For systems to be effective and widely accepted, the error rate in recognition and verification must approach zero.
Artificial Neural Networks, which simulate the human brain's operations, present themselves as a promising approach.
arXiv Detail & Related papers (2024-02-01T03:59:04Z) - Deep Learning-Based Approaches for Contactless Fingerprints Segmentation
and Extraction [1.2441902898414798]
We develop a deep learning-based segmentation tool for contactless fingerprint localization and segmentation.
In our evaluation, our segmentation method demonstrated an average mean absolute error (MAE) of 30 pixels, an error in angle prediction (EAP) of 5.92 degrees, and a labeling accuracy of 97.46%.
arXiv Detail & Related papers (2023-11-26T01:56:10Z) - Agile gesture recognition for capacitive sensing devices: adapting
on-the-job [55.40855017016652]
We demonstrate a hand gesture recognition system that uses signals from capacitive sensors embedded into the etee hand controller.
The controller generates real-time signals from each of the wearer five fingers.
We use a machine learning technique to analyse the time series signals and identify three features that can represent 5 fingers within 500 ms.
arXiv Detail & Related papers (2023-05-12T17:24:02Z) - A review of schemes for fingerprint image quality computation [66.32254395574994]
This paper reviews existing approaches for fingerprint image quality computation.
We also implement, test and compare a selection of them using the MCYT database including 9000 fingerprint images.
arXiv Detail & Related papers (2022-07-12T10:34:03Z) - On the vulnerability of fingerprint verification systems to fake
fingerprint attacks [57.36125468024803]
A medium-size fake fingerprint database is described and two different fingerprint verification systems are evaluated on it.
Results for an optical and a thermal sweeping sensors are given.
arXiv Detail & Related papers (2022-07-11T12:22:52Z) - A Method of Data Augmentation to Train a Small Area Fingerprint
Recognition Deep Neural Network with a Normal Fingerprint Database [0.0]
We propose a method of data augmentation to train a small-area fingerprint recognition deep neural network with a normal fingerprint database.
The experimental results showed the efficiency of our method.
arXiv Detail & Related papers (2022-03-23T07:29:39Z) - Responsible Disclosure of Generative Models Using Scalable
Fingerprinting [70.81987741132451]
Deep generative models have achieved a qualitatively new level of performance.
There are concerns on how this technology can be misused to spoof sensors, generate deep fakes, and enable misinformation at scale.
Our work enables a responsible disclosure of such state-of-the-art generative models, that allows researchers and companies to fingerprint their models.
arXiv Detail & Related papers (2020-12-16T03:51:54Z) - Latent Fingerprint Registration via Matching Densely Sampled Points [100.53031290339483]
Existing latent fingerprint registration approaches are mainly based on establishing correspondences between minutiae.
We propose a non-minutia latent fingerprint registration method which estimates the spatial transformation between a pair of fingerprints.
The proposed method achieves the state-of-the-art registration performance, especially under challenging conditions.
arXiv Detail & Related papers (2020-05-12T15:51:59Z) - An Overview of Fingerprint-Based Authentication: Liveness Detection and
Beyond [0.0]
We focus on methods to detect physical liveness, defined as techniques that can be used to ensure that a living human user is attempting to authenticate on a system.
We analyze how effective these methods are at preventing attacks where a malicious entity tries to trick a fingerprint-based authentication system to accept a fake finger as a real one.
arXiv Detail & Related papers (2020-01-24T20:07:53Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.